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TechBullion13h
Optimizing AI-Driven Decisions: A Comparative Look at Uplift Modeling and Reinforcement Learning
In the ever-evolving world of artificial intelligence (AI), the ability to make effective decisions is a cornerstone of ...
DeepSeek unveils new technique for smarter, scalable AI reward models
Reward models holding back AI? DeepSeek's SPCT creates self-guiding critiques, promising more scalable intelligence for enterprise LLMs.
What is reinforcement learning? An AI researcher explains a key method of teaching machines – and how it relates to training your dog
Animal trainers know that animal behavior can be influenced by rewarding desirable behaviors. A dog trainer gives the dog a treat when it does a trick correctly. This reinforces the behavior, and the ...
IEEE19d
Dynamically Optimize MTD Strategy in Satellite Computing Systems Using A2C Reinforcement Learning
In this paper, we propose a dynamic MTD strategy optimization scheme using Advantage Actor-Critic (A2C) reinforcement learning. Specifically, we formulate the MTD strategy optimization for SCS as a ...
techxplore23d
Legged robots skateboard successfully with reinforcement learning framework
With this transition information, the system can better estimate the states to assist the decision making." The new reinforcement learning framework Teng and his colleagues developed could soon open ...
IEEE25d
Solving the Vehicle Cooperation Problem at Signal-free Intersection via an Asynchronous Deep Reinforcement Learning Approach
Therefore, this study intends to solve the vehicle collaboration problem utilizing the deep reinforcement learning approach ... Then, a shared Advantage Actor-Critic (A2C) model is proposed to ...
marktechpost26d
ByteDance Research Releases DAPO: A Fully Open-Sourced LLM Reinforcement Learning System at Scale
Reinforcement learning (RL) has become central to advancing Large Language Models (LLMs), empowering them with improved reasoning capabilities necessary for complex tasks. However, the research ...